Overview

Brought to you by YData

Dataset statistics

Number of variables13
Number of observations2344
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory247.2 KiB
Average record size in memory108.0 B

Variable types

Numeric12
Categorical1

Alerts

Area is highly overall correlated with Convex_Area and 4 other fieldsHigh correlation
Aspect_Ration is highly overall correlated with Class_Çerçevelik and 5 other fieldsHigh correlation
Class_Çerçevelik is highly overall correlated with Aspect_Ration and 4 other fieldsHigh correlation
Compactness is highly overall correlated with Aspect_Ration and 5 other fieldsHigh correlation
Convex_Area is highly overall correlated with Area and 4 other fieldsHigh correlation
Eccentricity is highly overall correlated with Aspect_Ration and 5 other fieldsHigh correlation
Equiv_Diameter is highly overall correlated with Area and 4 other fieldsHigh correlation
Major_Axis_Length is highly overall correlated with Area and 8 other fieldsHigh correlation
Minor_Axis_Length is highly overall correlated with Area and 6 other fieldsHigh correlation
Perimeter is highly overall correlated with Area and 4 other fieldsHigh correlation
Roundness is highly overall correlated with Aspect_Ration and 6 other fieldsHigh correlation

Reproduction

Analysis started2024-09-28 21:07:40.525274
Analysis finished2024-09-28 21:08:01.893652
Duration21.37 seconds
Software versionydata-profiling vv4.10.0
Download configurationconfig.json

Variables

Area
Real number (ℝ)

HIGH CORRELATION 

Distinct2274
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean80630.958
Minimum47939
Maximum124268
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.6 KiB
2024-09-29T00:08:02.131729image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum47939
5-th percentile61100.75
Q171061.5
median79086
Q389541.75
95-th percentile104319.05
Maximum124268
Range76329
Interquartile range (IQR)18480.25

Descriptive statistics

Standard deviation13167.47
Coefficient of variation (CV)0.16330539
Kurtosis-0.28930394
Mean80630.958
Median Absolute Deviation (MAD)9084
Skewness0.39826913
Sum1.8899897 × 108
Variance1.7338226 × 108
MonotonicityNot monotonic
2024-09-29T00:08:02.324942image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
97268 3
 
0.1%
68063 3
 
0.1%
75637 3
 
0.1%
84130 2
 
0.1%
62105 2
 
0.1%
97062 2
 
0.1%
80595 2
 
0.1%
67675 2
 
0.1%
93313 2
 
0.1%
70952 2
 
0.1%
Other values (2264) 2321
99.0%
ValueCountFrequency (%)
47939 1
< 0.1%
49273 1
< 0.1%
50670 1
< 0.1%
50822 1
< 0.1%
51555 1
< 0.1%
52342 1
< 0.1%
52447 1
< 0.1%
52493 1
< 0.1%
52657 1
< 0.1%
52696 1
< 0.1%
ValueCountFrequency (%)
124268 1
< 0.1%
123618 1
< 0.1%
119880 1
< 0.1%
119467 1
< 0.1%
118751 1
< 0.1%
118283 1
< 0.1%
117831 1
< 0.1%
117620 1
< 0.1%
117550 1
< 0.1%
117469 1
< 0.1%

Perimeter
Real number (ℝ)

HIGH CORRELATION 

Distinct2337
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1127.9521
Minimum868.485
Maximum1468.224
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.6 KiB
2024-09-29T00:08:02.512067image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum868.485
5-th percentile964.9701
Q11049.0282
median1121.4275
Q31200.918
95-th percentile1312.6266
Maximum1468.224
Range599.739
Interquartile range (IQR)151.88975

Descriptive statistics

Standard deviation106.14962
Coefficient of variation (CV)0.094108274
Kurtosis-0.24662249
Mean1127.9521
Median Absolute Deviation (MAD)75.5405
Skewness0.32957874
Sum2643919.7
Variance11267.743
MonotonicityNot monotonic
2024-09-29T00:08:02.701862image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1206.002 2
 
0.1%
963.377 2
 
0.1%
1217.112 2
 
0.1%
1014.49 2
 
0.1%
1023.719 2
 
0.1%
1187.56 2
 
0.1%
1253.276 2
 
0.1%
1027.453 1
 
< 0.1%
1221.804 1
 
< 0.1%
1376.437 1
 
< 0.1%
Other values (2327) 2327
99.3%
ValueCountFrequency (%)
868.485 1
< 0.1%
871.458 1
< 0.1%
888.242 1
< 0.1%
889.398 1
< 0.1%
895.169 1
< 0.1%
899.493 1
< 0.1%
899.532 1
< 0.1%
902.59 1
< 0.1%
903.456 1
< 0.1%
904.075 1
< 0.1%
ValueCountFrequency (%)
1468.224 1
< 0.1%
1453.922 1
< 0.1%
1448.55 1
< 0.1%
1443.597 1
< 0.1%
1443.428 1
< 0.1%
1439.456 1
< 0.1%
1432.89 1
< 0.1%
1430.169 1
< 0.1%
1425.395 1
< 0.1%
1419.753 1
< 0.1%

Major_Axis_Length
Real number (ℝ)

HIGH CORRELATION 

Distinct2343
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean455.90289
Minimum324.0113
Maximum632.108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.6 KiB
2024-09-29T00:08:02.888859image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum324.0113
5-th percentile378.44298
Q1415.38038
median449.86205
Q3491.64882
95-th percentile551.66063
Maximum632.108
Range308.0967
Interquartile range (IQR)76.26845

Descriptive statistics

Standard deviation54.261334
Coefficient of variation (CV)0.1190195
Kurtosis-0.14960038
Mean455.90289
Median Absolute Deviation (MAD)37.48055
Skewness0.45121699
Sum1068636.4
Variance2944.2924
MonotonicityNot monotonic
2024-09-29T00:08:03.078599image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
465.7347 2
 
0.1%
326.1485 1
 
< 0.1%
521.4462 1
 
< 0.1%
565.7508 1
 
< 0.1%
555.5923 1
 
< 0.1%
511.3968 1
 
< 0.1%
542.1107 1
 
< 0.1%
469.7542 1
 
< 0.1%
517.9383 1
 
< 0.1%
478.8952 1
 
< 0.1%
Other values (2333) 2333
99.5%
ValueCountFrequency (%)
324.0113 1
< 0.1%
326.1485 1
< 0.1%
329.9696 1
< 0.1%
331.6936 1
< 0.1%
334.1895 1
< 0.1%
340.6951 1
< 0.1%
342.3154 1
< 0.1%
342.5092 1
< 0.1%
343.0318 1
< 0.1%
343.189 1
< 0.1%
ValueCountFrequency (%)
632.108 1
< 0.1%
629.723 1
< 0.1%
622.8818 1
< 0.1%
621.2633 1
< 0.1%
620.0968 1
< 0.1%
619.1037 1
< 0.1%
616.5789 1
< 0.1%
616.0277 1
< 0.1%
614.8959 1
< 0.1%
613.415 1
< 0.1%

Minor_Axis_Length
Real number (ℝ)

HIGH CORRELATION 

Distinct2341
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean225.98503
Minimum163.8458
Maximum292.6174
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.6 KiB
2024-09-29T00:08:03.240889image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum163.8458
5-th percentile189.17492
Q1211.61147
median224.8573
Q3240.23622
95-th percentile264.52314
Maximum292.6174
Range128.7716
Interquartile range (IQR)28.62475

Descriptive statistics

Standard deviation22.335848
Coefficient of variation (CV)0.098837733
Kurtosis-0.11502682
Mean225.98503
Median Absolute Deviation (MAD)14.12945
Skewness0.12308303
Sum529708.92
Variance498.89013
MonotonicityNot monotonic
2024-09-29T00:08:03.418329image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
220.6852 2
 
0.1%
221.2116 2
 
0.1%
229.4863 2
 
0.1%
220.2388 1
 
< 0.1%
237.373 1
 
< 0.1%
248.3426 1
 
< 0.1%
245.516 1
 
< 0.1%
215.8945 1
 
< 0.1%
194.3435 1
 
< 0.1%
230.8967 1
 
< 0.1%
Other values (2331) 2331
99.4%
ValueCountFrequency (%)
163.8458 1
< 0.1%
164.7038 1
< 0.1%
165.8306 1
< 0.1%
166.4057 1
< 0.1%
167.2736 1
< 0.1%
167.833 1
< 0.1%
168.2948 1
< 0.1%
170.1357 1
< 0.1%
170.1768 1
< 0.1%
170.2289 1
< 0.1%
ValueCountFrequency (%)
292.6174 1
< 0.1%
292.53 1
< 0.1%
292.4844 1
< 0.1%
289.9712 1
< 0.1%
289.1724 1
< 0.1%
288.6814 1
< 0.1%
288.5734 1
< 0.1%
287.8763 1
< 0.1%
285.4023 1
< 0.1%
284.5436 1
< 0.1%

Convex_Area
Real number (ℝ)

HIGH CORRELATION 

Distinct2292
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean81448.702
Minimum48366
Maximum125239
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.6 KiB
2024-09-29T00:08:03.580131image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum48366
5-th percentile61754.5
Q171763.75
median79869.5
Q390511.25
95-th percentile105533.55
Maximum125239
Range76873
Interquartile range (IQR)18747.5

Descriptive statistics

Standard deviation13273.366
Coefficient of variation (CV)0.16296597
Kurtosis-0.29547066
Mean81448.702
Median Absolute Deviation (MAD)9120.5
Skewness0.39454903
Sum1.9091576 × 108
Variance1.7618225 × 108
MonotonicityNot monotonic
2024-09-29T00:08:03.977444image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
77745 3
 
0.1%
76640 3
 
0.1%
74461 2
 
0.1%
107393 2
 
0.1%
68853 2
 
0.1%
54979 2
 
0.1%
73556 2
 
0.1%
86515 2
 
0.1%
67373 2
 
0.1%
79445 2
 
0.1%
Other values (2282) 2322
99.1%
ValueCountFrequency (%)
48366 1
< 0.1%
49739 1
< 0.1%
51092 1
< 0.1%
51648 1
< 0.1%
52013 1
< 0.1%
52796 1
< 0.1%
52958 2
0.1%
53093 1
< 0.1%
53159 1
< 0.1%
53437 1
< 0.1%
ValueCountFrequency (%)
125239 1
< 0.1%
124662 1
< 0.1%
120796 1
< 0.1%
120581 1
< 0.1%
120036 1
< 0.1%
119270 1
< 0.1%
118597 1
< 0.1%
118591 1
< 0.1%
118565 1
< 0.1%
118327 1
< 0.1%

Equiv_Diameter
Real number (ℝ)

HIGH CORRELATION 

Distinct2274
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean319.35438
Minimum247.0584
Maximum397.7725
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.6 KiB
2024-09-29T00:08:04.216321image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum247.0584
5-th percentile278.91911
Q1300.79613
median317.32545
Q3337.65088
95-th percentile364.44909
Maximum397.7725
Range150.7141
Interquartile range (IQR)36.85475

Descriptive statistics

Standard deviation25.992151
Coefficient of variation (CV)0.081389681
Kurtosis-0.40929789
Mean319.35438
Median Absolute Deviation (MAD)18.31455
Skewness0.21170442
Sum748566.67
Variance675.59192
MonotonicityNot monotonic
2024-09-29T00:08:04.641345image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
351.9168 3
 
0.1%
294.3816 3
 
0.1%
310.3289 3
 
0.1%
327.2883 2
 
0.1%
281.202 2
 
0.1%
351.544 2
 
0.1%
320.3385 2
 
0.1%
293.5413 2
 
0.1%
344.688 2
 
0.1%
300.5643 2
 
0.1%
Other values (2264) 2321
99.0%
ValueCountFrequency (%)
247.0584 1
< 0.1%
250.4722 1
< 0.1%
253.9981 1
< 0.1%
254.3788 1
< 0.1%
256.2067 1
< 0.1%
258.1548 1
< 0.1%
258.4136 1
< 0.1%
258.5269 1
< 0.1%
258.9304 1
< 0.1%
259.0263 1
< 0.1%
ValueCountFrequency (%)
397.7725 1
< 0.1%
396.7308 1
< 0.1%
390.6865 1
< 0.1%
390.013 1
< 0.1%
388.8425 1
< 0.1%
388.0755 1
< 0.1%
387.3333 1
< 0.1%
386.9864 1
< 0.1%
386.8712 1
< 0.1%
386.7379 1
< 0.1%

Eccentricity
Real number (ℝ)

HIGH CORRELATION 

Distinct1239
Distinct (%)52.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.86091378
Minimum0.7252
Maximum0.9464
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.6 KiB
2024-09-29T00:08:05.065718image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.7252
5-th percentile0.78676
Q10.8321
median0.8634
Q30.895125
95-th percentile0.922785
Maximum0.9464
Range0.2212
Interquartile range (IQR)0.063025

Descriptive statistics

Standard deviation0.042420284
Coefficient of variation (CV)0.049273556
Kurtosis-0.34132399
Mean0.86091378
Median Absolute Deviation (MAD)0.0315
Skewness-0.42465075
Sum2017.9819
Variance0.0017994805
MonotonicityNot monotonic
2024-09-29T00:08:05.444211image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.8495 7
 
0.3%
0.8834 7
 
0.3%
0.8504 6
 
0.3%
0.8987 6
 
0.3%
0.8915 6
 
0.3%
0.8828 6
 
0.3%
0.8535 6
 
0.3%
0.8985 6
 
0.3%
0.8914 6
 
0.3%
0.8433 6
 
0.3%
Other values (1229) 2282
97.4%
ValueCountFrequency (%)
0.7252 1
< 0.1%
0.7272 1
< 0.1%
0.7275 1
< 0.1%
0.7284 1
< 0.1%
0.7319 1
< 0.1%
0.7348 1
< 0.1%
0.7376 1
< 0.1%
0.7382 1
< 0.1%
0.7398 1
< 0.1%
0.7403 1
< 0.1%
ValueCountFrequency (%)
0.9464 1
< 0.1%
0.9429 1
< 0.1%
0.9428 1
< 0.1%
0.942 1
< 0.1%
0.9412 1
< 0.1%
0.9409 1
< 0.1%
0.9407 1
< 0.1%
0.9405 1
< 0.1%
0.9398 2
0.1%
0.9393 1
< 0.1%

Solidity
Real number (ℝ)

Distinct110
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.98991271
Minimum0.9831
Maximum0.9944
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.6 KiB
2024-09-29T00:08:05.860758image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.9831
5-th percentile0.9857
Q10.9886
median0.9904
Q30.9916
95-th percentile0.9928
Maximum0.9944
Range0.0113
Interquartile range (IQR)0.003

Descriptive statistics

Standard deviation0.0022104243
Coefficient of variation (CV)0.0022329487
Kurtosis0.055856385
Mean0.98991271
Median Absolute Deviation (MAD)0.0014
Skewness-0.73492338
Sum2320.3554
Variance4.8859757 × 10-6
MonotonicityNot monotonic
2024-09-29T00:08:06.156404image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.9912 60
 
2.6%
0.9905 58
 
2.5%
0.9916 57
 
2.4%
0.9906 55
 
2.3%
0.9911 54
 
2.3%
0.9904 52
 
2.2%
0.9918 52
 
2.2%
0.9909 52
 
2.2%
0.9913 51
 
2.2%
0.9914 49
 
2.1%
Other values (100) 1804
77.0%
ValueCountFrequency (%)
0.9831 4
0.2%
0.9832 3
 
0.1%
0.9833 3
 
0.1%
0.9834 4
0.2%
0.9835 4
0.2%
0.9837 2
 
0.1%
0.9838 2
 
0.1%
0.9839 3
 
0.1%
0.984 8
0.3%
0.9841 3
 
0.1%
ValueCountFrequency (%)
0.9944 1
 
< 0.1%
0.9943 1
 
< 0.1%
0.9939 2
 
0.1%
0.9938 6
 
0.3%
0.9937 8
 
0.3%
0.9936 11
0.5%
0.9935 8
 
0.3%
0.9934 11
0.5%
0.9933 5
 
0.2%
0.9932 20
0.9%

Extent
Real number (ℝ)

Distinct1318
Distinct (%)56.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.69645644
Minimum0.5333
Maximum0.8296
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.6 KiB
2024-09-29T00:08:06.356863image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.5333
5-th percentile0.578775
Q10.662375
median0.7147
Q30.7405
95-th percentile0.7623
Maximum0.8296
Range0.2963
Interquartile range (IQR)0.078125

Descriptive statistics

Standard deviation0.056673594
Coefficient of variation (CV)0.081374212
Kurtosis0.032128441
Mean0.69645644
Median Absolute Deviation (MAD)0.0319
Skewness-0.91944818
Sum1632.4939
Variance0.0032118963
MonotonicityNot monotonic
2024-09-29T00:08:06.596750image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.7249 8
 
0.3%
0.7445 8
 
0.3%
0.7403 8
 
0.3%
0.7424 7
 
0.3%
0.7379 7
 
0.3%
0.7201 7
 
0.3%
0.7393 7
 
0.3%
0.7435 7
 
0.3%
0.7325 7
 
0.3%
0.744 6
 
0.3%
Other values (1308) 2272
96.9%
ValueCountFrequency (%)
0.5333 1
< 0.1%
0.5347 1
< 0.1%
0.5352 1
< 0.1%
0.5353 1
< 0.1%
0.5361 1
< 0.1%
0.5362 1
< 0.1%
0.5387 1
< 0.1%
0.5394 1
< 0.1%
0.541 2
0.1%
0.5415 1
< 0.1%
ValueCountFrequency (%)
0.8296 1
< 0.1%
0.7993 1
< 0.1%
0.7879 1
< 0.1%
0.7831 1
< 0.1%
0.7824 1
< 0.1%
0.7814 1
< 0.1%
0.781 1
< 0.1%
0.7808 1
< 0.1%
0.7799 1
< 0.1%
0.7797 1
< 0.1%

Roundness
Real number (ℝ)

HIGH CORRELATION 

Distinct1396
Distinct (%)59.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.79468204
Minimum0.6327
Maximum0.9221
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.6 KiB
2024-09-29T00:08:06.786644image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.6327
5-th percentile0.70036
Q10.757075
median0.7995
Q30.8357
95-th percentile0.873485
Maximum0.9221
Range0.2894
Interquartile range (IQR)0.078625

Descriptive statistics

Standard deviation0.053019202
Coefficient of variation (CV)0.066717504
Kurtosis-0.42489719
Mean0.79468204
Median Absolute Deviation (MAD)0.0386
Skewness-0.32853544
Sum1862.7347
Variance0.0028110358
MonotonicityNot monotonic
2024-09-29T00:08:07.015539image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.7609 7
 
0.3%
0.7933 6
 
0.3%
0.8028 6
 
0.3%
0.835 6
 
0.3%
0.8357 6
 
0.3%
0.8267 6
 
0.3%
0.7413 5
 
0.2%
0.806 5
 
0.2%
0.7749 5
 
0.2%
0.8568 5
 
0.2%
Other values (1386) 2287
97.6%
ValueCountFrequency (%)
0.6327 1
< 0.1%
0.6338 1
< 0.1%
0.6374 1
< 0.1%
0.6426 1
< 0.1%
0.644 1
< 0.1%
0.6457 1
< 0.1%
0.6485 1
< 0.1%
0.6515 1
< 0.1%
0.6516 1
< 0.1%
0.6541 1
< 0.1%
ValueCountFrequency (%)
0.9221 1
< 0.1%
0.9162 1
< 0.1%
0.9161 1
< 0.1%
0.916 1
< 0.1%
0.9154 1
< 0.1%
0.9147 1
< 0.1%
0.9118 1
< 0.1%
0.9057 1
< 0.1%
0.9045 1
< 0.1%
0.9044 1
< 0.1%

Aspect_Ration
Real number (ℝ)

HIGH CORRELATION 

Distinct2100
Distinct (%)89.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0348581
Minimum1.4524
Maximum3.0969
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.6 KiB
2024-09-29T00:08:07.250006image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1.4524
5-th percentile1.620095
Q11.80315
median1.9823
Q32.242825
95-th percentile2.594925
Maximum3.0969
Range1.6445
Interquartile range (IQR)0.439675

Descriptive statistics

Standard deviation0.30145748
Coefficient of variation (CV)0.14814668
Kurtosis-0.25671512
Mean2.0348581
Median Absolute Deviation (MAD)0.2108
Skewness0.55376638
Sum4769.7075
Variance0.09087661
MonotonicityNot monotonic
2024-09-29T00:08:07.549603image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.8606 4
 
0.2%
1.8491 4
 
0.2%
1.8955 3
 
0.1%
2.6286 3
 
0.1%
1.8275 3
 
0.1%
1.9006 3
 
0.1%
1.8281 3
 
0.1%
1.806 3
 
0.1%
1.8285 3
 
0.1%
1.7601 3
 
0.1%
Other values (2090) 2312
98.6%
ValueCountFrequency (%)
1.4524 1
< 0.1%
1.4569 1
< 0.1%
1.4575 1
< 0.1%
1.4595 1
< 0.1%
1.4675 1
< 0.1%
1.4743 1
< 0.1%
1.4809 1
< 0.1%
1.4825 1
< 0.1%
1.4864 1
< 0.1%
1.4876 1
< 0.1%
ValueCountFrequency (%)
3.0969 1
< 0.1%
3.0017 1
< 0.1%
2.9988 1
< 0.1%
2.9789 1
< 0.1%
2.9593 1
< 0.1%
2.9521 1
< 0.1%
2.9478 1
< 0.1%
2.9435 1
< 0.1%
2.9271 1
< 0.1%
2.9263 1
< 0.1%

Compactness
Real number (ℝ)

HIGH CORRELATION 

Distinct1340
Distinct (%)57.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.70489851
Minimum0.567
Maximum0.8289
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.6 KiB
2024-09-29T00:08:07.850788image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.567
5-th percentile0.619215
Q10.665975
median0.7085
Q30.743225
95-th percentile0.7842
Maximum0.8289
Range0.2619
Interquartile range (IQR)0.07725

Descriptive statistics

Standard deviation0.050737263
Coefficient of variation (CV)0.071978111
Kurtosis-0.65482954
Mean0.70489851
Median Absolute Deviation (MAD)0.0379
Skewness-0.11265776
Sum1652.2821
Variance0.0025742698
MonotonicityNot monotonic
2024-09-29T00:08:08.016804image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.7264 7
 
0.3%
0.7073 7
 
0.3%
0.7414 6
 
0.3%
0.7435 6
 
0.3%
0.7518 6
 
0.3%
0.7077 6
 
0.3%
0.7093 6
 
0.3%
0.6851 6
 
0.3%
0.7097 5
 
0.2%
0.6989 5
 
0.2%
Other values (1330) 2284
97.4%
ValueCountFrequency (%)
0.567 1
< 0.1%
0.5753 1
< 0.1%
0.5768 1
< 0.1%
0.5785 1
< 0.1%
0.5789 1
< 0.1%
0.5797 1
< 0.1%
0.5801 1
< 0.1%
0.5805 2
0.1%
0.581 1
< 0.1%
0.5828 1
< 0.1%
ValueCountFrequency (%)
0.8289 1
< 0.1%
0.827 1
< 0.1%
0.8256 1
< 0.1%
0.8253 1
< 0.1%
0.8247 1
< 0.1%
0.8213 1
< 0.1%
0.8209 1
< 0.1%
0.8207 1
< 0.1%
0.8189 1
< 0.1%
0.8184 1
< 0.1%

Class_Çerçevelik
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size36.6 KiB
1
1228 
0
1116 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2344
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 1228
52.4%
0 1116
47.6%

Length

2024-09-29T00:08:08.155702image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-09-29T00:08:08.257625image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1228
52.4%
0 1116
47.6%

Most occurring characters

ValueCountFrequency (%)
1 1228
52.4%
0 1116
47.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2344
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 1228
52.4%
0 1116
47.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2344
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 1228
52.4%
0 1116
47.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2344
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 1228
52.4%
0 1116
47.6%

Interactions

2024-09-29T00:07:59.785707image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:41.094863image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:43.577302image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:45.395080image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:47.004338image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:48.457952image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:50.051342image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:51.459993image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:52.954609image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:54.622146image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:56.343516image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:58.074080image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:59.918553image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:41.240071image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:43.764868image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:45.542610image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:47.175579image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:48.582165image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:50.158594image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:51.697185image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:53.071567image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:54.762870image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:56.461211image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:58.208986image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:08:00.114389image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:41.396936image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:43.999785image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:45.656730image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:47.303908image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:48.850588image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:50.260447image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:51.826983image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:53.241375image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:54.880905image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:56.572449image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:58.335667image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:08:00.258067image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:41.562826image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:44.182076image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:45.768451image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:47.429719image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:48.955962image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:50.367042image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:51.938955image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:53.378263image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:55.007595image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:56.690381image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:58.488151image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:08:00.395750image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:41.722265image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:44.319782image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:45.884353image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:47.544524image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:49.066599image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:50.469537image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:52.059130image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:53.538392image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:55.317725image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:56.834019image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:58.627354image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:08:00.513820image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:41.888211image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:44.440346image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:46.139338image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:47.666734image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:49.190957image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:50.594086image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:52.177932image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:53.695295image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:55.437908image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:57.045571image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:58.772747image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:08:00.656672image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:42.063597image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:44.569854image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:46.293889image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:47.799925image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:49.340125image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:50.714116image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:52.290574image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:53.911132image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:55.605421image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:57.234435image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:58.947531image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:08:00.817959image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:42.256468image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:44.679258image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:46.404267image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:47.909420image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:49.455394image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:50.827425image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:52.387896image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:54.036792image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:55.745393image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:57.487617image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:59.063339image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:08:00.942230image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:42.390882image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:44.793177image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:46.512998image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:48.024993image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:49.600020image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:50.938941image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:52.521504image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:54.148600image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:55.878433image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:57.617077image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:59.216738image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:08:01.063519image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:42.776242image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:44.926955image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:46.625636image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:48.135131image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:49.725775image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:51.063942image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:52.632091image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:54.266752image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:56.008690image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:57.737644image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:59.378258image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:08:01.183988image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:43.269802image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:45.068672image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:46.775909image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:48.248637image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:49.838246image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:51.207472image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:52.736980image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:54.375606image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:56.122579image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:57.851397image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:59.527687image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:08:01.300107image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:43.432892image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:45.251754image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:46.893361image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:48.355364image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:49.951360image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:51.335012image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:52.849174image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:54.496838image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:56.242899image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:57.967947image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-29T00:07:59.660565image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Correlations

2024-09-29T00:08:08.336789image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
AreaAspect_RationClass_ÇerçevelikCompactnessConvex_AreaEccentricityEquiv_DiameterExtentMajor_Axis_LengthMinor_Axis_LengthPerimeterRoundnessSolidity
Area1.0000.1690.253-0.1671.0000.1691.0000.0300.7860.6800.932-0.1850.151
Aspect_Ration0.1691.0000.758-1.0000.1691.0000.169-0.1770.720-0.5730.476-0.9630.047
Class_Çerçevelik0.2530.7581.0000.7640.2520.7580.2540.3450.5660.4420.3990.7150.182
Compactness-0.167-1.0000.7641.000-0.167-1.000-0.1670.178-0.7190.573-0.4760.965-0.039
Convex_Area1.0000.1690.252-0.1671.0000.1681.0000.0290.7860.6800.933-0.1870.139
Eccentricity0.1691.0000.758-1.0000.1681.0000.169-0.1770.720-0.5730.476-0.9630.047
Equiv_Diameter1.0000.1690.254-0.1671.0000.1691.0000.0300.7860.6800.932-0.1850.151
Extent0.030-0.1770.3450.1780.029-0.1770.0301.000-0.0860.138-0.0390.2000.086
Major_Axis_Length0.7860.7200.566-0.7190.7860.7200.786-0.0861.0000.1120.946-0.7120.123
Minor_Axis_Length0.680-0.5730.4420.5730.680-0.5730.6800.1380.1121.0000.3970.5320.096
Perimeter0.9320.4760.399-0.4760.9330.4760.932-0.0390.9460.3971.000-0.5050.090
Roundness-0.185-0.9630.7150.965-0.187-0.963-0.1850.200-0.7120.532-0.5051.0000.103
Solidity0.1510.0470.182-0.0390.1390.0470.1510.0860.1230.0960.0900.1031.000

Missing values

2024-09-29T00:08:01.489490image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-09-29T00:08:01.776984image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

AreaPerimeterMajor_Axis_LengthMinor_Axis_LengthConvex_AreaEquiv_DiameterEccentricitySolidityExtentRoundnessAspect_RationCompactnessClass_Çerçevelik
056276888.242326.1485220.238856831267.68050.73760.99020.74530.89631.48090.82071
1766311068.146417.1932234.228977280312.36140.82750.99160.71510.84401.78110.74871
2716231082.987435.8328211.045772663301.98220.87490.98570.74000.76742.06510.69291
366458992.051381.5638222.532267118290.88990.81230.99020.73960.84861.71460.76241
466107998.146383.8883220.454567117290.12070.81870.98500.67520.83381.74130.75571
5731911041.460405.8132231.426173969305.26980.82150.98950.71650.84801.75350.75221
6733381020.055392.2516238.549473859305.57620.79380.99290.71870.88571.64430.77901
7696921049.108421.4875211.770770442297.88360.86460.98940.67360.79571.99030.70671
8957271231.609488.1199251.308696831349.11800.85730.98860.61880.79301.94230.71521
9734651047.767413.6504227.264474089305.84070.83560.99160.74430.84091.82010.73941
AreaPerimeterMajor_Axis_LengthMinor_Axis_LengthConvex_AreaEquiv_DiameterEccentricitySolidityExtentRoundnessAspect_RationCompactnessClass_Çerçevelik
2489928861211.852501.5779237.121393503343.89840.88120.99340.61800.79482.11530.68560
249051555934.911401.8321164.703852013256.20670.91210.99120.71870.74122.43970.63760
2491698361010.605396.6286224.791870419298.19110.82390.99170.66930.85931.76440.75180
2492842361274.656456.9323237.154085248327.49440.85480.98810.61040.65151.92670.71670
249358987977.410404.0779186.371059518274.05220.88730.99110.73270.77592.16810.67820
2494797551146.431470.3888217.829680649318.66470.88630.98890.71750.76262.15940.67740
2496696471084.318462.9416191.821070216297.78740.91010.99190.60020.74442.41340.64330
2497879941210.314507.2200222.187288702334.71990.89900.99200.76430.75492.28280.65990
2498800111182.947501.9065204.753180902319.17580.91300.98900.73740.71852.45130.63590
2499849341159.933462.8951234.559785781328.84850.86210.99010.73600.79331.97350.71040